TY  - JOUR
AU  - Pallast, Niklas
AU  - Diedenhofen, Michael
AU  - Blaschke, Stefan
AU  - Wieters, Frederique
AU  - Wiedermann, Dirk
AU  - Hoehn, Mathias
AU  - Fink, Gereon R.
AU  - Aswendt, Markus
TI  - Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri)
JO  - Frontiers in neuroinformatics
VL  - 13
SN  - 1662-5196
CY  - Lausanne
PB  - Frontiers Research Foundation
M1  - FZJ-2019-03625
SP  - 42
PY  - 2019
AB  - Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution microscopy and ex vivo molecular techniques. Brain mapping, the correlation of corresponding regions between multiple brains in a standard brain atlas system, is widely used in human MRI. For small animal MRI, however, there is no scientific consensus on pre-processing strategies and atlas-based neuroinformatics. Thus, it remains difficult to compare and validate results from different pre-clinical studies which were processed using custom-made code or individual adjustments of clinical MRI software and without a standard brain reference atlas. Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). The AIDAmri pipeline includes automated pre-processing steps, such as raw data conversion, skull-stripping and bias-field correction as well as image registration with the Allen Mouse Brain Reference Atlas (ARA). Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. Each processing step was optimized for efficient data processing requiring minimal user-input and user programming skills. The raw data is analyzed and results transferred to the ARA coordinate system in order to allow an efficient and highly-accurate region-based analysis. AIDAmri is intended to fill the gap of a missing open-access and cross-platform toolbox for the most relevant mouse brain MRI sequences thereby facilitating data processing in large cohorts and multi-center studies.
LB  - PUB:(DE-HGF)16
C6  - pmid:31231202
UR  - <Go to ISI:>//WOS:000470291200003
DO  - DOI:10.3389/fninf.2019.00042
UR  - https://juser.fz-juelich.de/record/863613
ER  -